War-torn regions reveal a lot about the sentiments of people suffering and striving for peace. A comprehensive report [1]} on Kashmir (disputed territory) revealed instances of hope speech in YouTube comments after the Pulwama terror attack on February 14, 2019. Palakodety et al. (2020) [1]} constructed a multilingual dataset of YouTube comments in English and Hindi written in Roman and Devanagari scripts, respectively. They used a combination of polyglot embeddings from FastText (100-dimensions), sentiment score, and n-grams (1-3) with Logistic Regression (LR) to achieve the best averaged-macro F1-score of 78.51 (\(\pm \)  2.24%). They modeled hope speech detection as a positive comment mining task (positive/negative sentiments) which shows a very shallow understanding of hope as a subject. In reality, hope is a broad phenomenon with various emotions.
